Incremental map generation, refinement and extension with GPS traces

ABSTRACT

A method for improving and extending an existing road network and generating new networks from statistically relevant amounts of probe data recorded by GPS-enabled navigation devices. New probe data is matched to the existing digital vector map, then the data merged into the existing network using a weighted mean technique. When new roads are detected, appropriate junction points are made with the existing network elements. The updated network data is simplified to improve computing speed and reduce data storage requirements.

CROSS CROSS-REFERENCES TO RELATED APPLICATIONS

This application is the National Stage of International Application No.PCT/EP2009/063938, filed Oct. 22, 2009 and designating the UnitedStates. The entire content of this application is incorporated herein byreference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to a method for updating and extendingdigital vector maps using probe data, and more particularly toward amethod for improving digital roadway and pathway maps using GPScoordinates generated by one or more personal navigation devices.

2. Related Art

Navigation systems, electronic maps (also known as digital maps), andgeographical positioning devices are increasingly used by travelers toassist with various navigation functions, such as to determine theoverall position and orientation of the traveler and/or vehicle, finddestinations and addresses, calculate optimal routes, and providereal-time driving guidance. Typically, the navigation system includes asmall display screen or graphic user interface that portrays a networkof streets as a series of line segments, including a centre-line runningapproximately along the centre of each street or path. The traveler canthen be generally located on the digital map close to or with regard tothat centre-line.

Digital maps are expensive to produce and update, since exhibiting andprocessing road information is very costly. Surveying methods ordigitizing satellite images are commonly employed techniques forcreating a digital map. Furthermore, digital maps are likely to containinaccuracies or systematic errors due to faulty or inaccurate inputsources or flawed inference procedures. Once a digital map has beencreated, it is costly to keep map information up to date, since roadgeometry changes over time. In some regions of the world, digital mapsare not available at all.

FIGS. 1A-1C depict a digital vector map in the form of roads. FIG. 1Arepresents major motorways or driving routes. FIG. 1B depicts the majormotorways of FIG. 1A plus an interconnecting network of secondary roads.FIG. 1C illustrates all of the information of FIG. 1B together with anextended network of tertiary streets and alleys. As will be appreciatedby reference to these figures, in combination with the expense andeffort required to produce digital maps, it may be the case that anexisting roadway map or network is incomplete in its depiction of allroadways or paths within a given region. Furthermore, due to theevolving nature of networks which may include but are not limited toroadways and paths, changes may occur over time such that an existingdigital map may no longer accurately portray current conditions.

In FIG. 2, a digital vector map contains junctions J and line segmentsw₁ . . . w₉. Together, they constitute a graph with several additionalproperties. The junctions J are the nodes and the line segments w arethe edges of the graph. For a unidirectional map the graph is directedand for a bidirectional map it is undirected. Every line segment wconnects two junctions J. On the contrary, in each junction J meets justone or least three line segments w. (Only in exceptional cases will twoline segments meet in a junction.) The junctions J and the line segmentsw are usually associated with several attributes, including for exampleweight value, measure and heading. The geometry of a line segment w isoften described as a polygonal chain (also called polygonal curve,polygonal path, or piecewise linear curve). Alternatively one can alsouse other curves like splines, circle segments or clothoids. Howeverbecause each curve can be sufficiently accurately approximated through apolygonal chain, usually polygonal chains are used. The vertices ornodes of a polygonal chain are called shape points SP because theydefine the shape of the curve. Of course, it is possible to change ashape point SP to a junction J under appropriate circumstances, forexample if an attribute changes.

FIG. 2 illustrates a fractional section of a digital vector map, in thiscase a bi-directional roadway supporting two-way traffic. A main trunkof the roadway is indicated at 10 and a branch road extending generallyperpendicularly from the main trunk 10 is indicated at 12. It is known,for example, to take probe data inputs from low-cost positioning systemsand handheld devices and mobile phones with integrated GPS functionalityfor the purpose of incrementally learning a map using certain clusteringtechnologies. The input to be processed consists of recorded GPS tracesin the form of a standard ASCII stream, which is supported by almost allexisting GPS devices. The output is a road map in the form of a directedgraph with nodes and edges annotated with travel time information.Travelers appropriately fitted with navigation devices and traversingthe main trunk 10 and branch 12 junction may thus create a trace maplike that shown in FIG. 4, with nodes created at regular distances. Thenodes and edges are stored in a digital vector map table or database.Through this technique which represents an incremental approach, roadgeometry can be inferred, and the collected data points refined byfiltering and partitioning algorithms. For more complete discussion onthis technique, reference is made to “Incremental Map Generaltion withGPS Traces,” , Briintrup, R., Edelkamp, S., Jabbar, S., Scholz, B.,Proc. 8th Int. IEEE Conf. on Intelligent Transportation Systems, Vienna,Austria, 2005, Pages 413-418.

Another technique developed by H.-U. Otto and O. Schmelzle of Tele AtlasB. V., based on a local approach, generates a new road network fromprobe data. This approach is based on the technique of following eachtrace and looking into the buffer around separate trace points toestablish the line segments. New network elements, e.g., roadways orpathways, are generated depending on the distribution of the data pointsinside the buffer and the associated directions of vectors. While thistechnique is useful in generating new maps using GPS traces or otherprobe data, it is not well suited to improving existing networks.

Accordingly, there is a need for an improved method to receive probedata such as that from GPS-enabled navigation devices, for the purposeof improving existing networks and generating new network elements suchas employed in the practice of digital map making.

SUMMARY OF THE INVENTION

This invention overcomes the shortcomings and deficiencies of thevarious prior art techniques by providing a method for generating,refining and extending digital vector maps using any type of traces, butmost preferably GPS traces, from probe data. The method comprises thesteps of: providing a digital vector map configured to store a pluralityof line segments spatially associated within a coordinate system;associating each line segment in the digital vector map with a weightvalue; collecting at least one GPS trace from a plurality ofsequentially transmitted probe data points; establishing a map matchingcriteria; and comparing each probe data point along the GPS trace to theline segments in the digital vector map using the map matching criteria.The method is characterized by: designating as “matched” to at least oneline segment each probe data point along the GPS trace that meets themap matching criteria while designating as “unmatched” each probe datapoint along the GPS trace that fails the map matching criteria;associating the portion of the GPS trace containing matched probe datapoints to the respective line segments (if any) of the digital vectormap; computing a centre-line between the respective line segment and anyportion of the GPS trace containing corresponding matched probe datapoints using the weight value of the line segment; replacing the linesegment through the centre-line; and creating a new line segment in thedigital vector map with the portion of the GPS trace containingunmatched probe data points.

The map matching criteria can be established in a variety of suitableways. According to one method, an offset distance is calculated betweeneach probe data point and a line segment in the digital vector map. Apredetermined maximum offset value is also established, and probe datapoints which have a calculated offset distance smaller than the maximumoffset value are designated as matched probe data points. Conversely,probe data points which have a calculated offset distance larger thanthe maximum offset value are designated as unmatched probe data points.

By this method, an already existing digital vector map, such as thatused for road maps, bicycle maps and footpath maps and the like, can beimproved using collected probe data. The improved quality of the digitalvector map can be used to more accurately detect branches, merges andcrossings in the digital vector map, may be used to generate bothunidirectional and bidirectional networks, and represents a substantialefficiency improvement when computing large amounts of probe data over alarge network area. Furthermore, the general concepts of this inventioncan be used to improve any digital vector map, not only roadway andpathway maps. For example, circuit diagrams, schematics, and othergraphical representations that can be spatially associated within acoordinate system may benefit from the techniques of this invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-C depict a roadway network as representative of one form ofdigital vector map wherein FIG. 1A shows the major roadways, FIG. 1Bshows the interconnecting network and FIG. 1C depicts a street network;

FIG. 2 is simplified depiction of a digital vector map showing itsjunctions, line segments, and shape points;

FIG. 3 is a schematic diagram depicting an overview of the subjectmethod wherein probe data is collected from a plurality of GPS-enablednavigation devices, stored in a table, and then matched to line segmentsin a preexisting digital vector map for the purpose of improving and/orextending the digital vector map;

FIG. 4 is an illustration of the manner in which a trace line resultingfrom probe data points is initially set in a coordinate system alongside the preexisting elements in a digital vector map;

FIG. 5 is a view as in FIG. 4, but depicting the calculation of measuresand offset distances between line segments in the digital vector map andthe collected data points;

FIG. 6 is an enlarged view from FIG. 5 depicting the optional splitpoints from which new junctions may be inserted to a digital vector map;

FIG. 7 is an enlarged view of the area circumscribed at 7 in FIG. 6 andrelated to the step of computing a new junction in order to split a linesegment; and

FIG. 8 depicts an updated digital vector map using the techniques ofthis invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Referring to the figures, wherein like numerals indicate like orcorresponding parts throughout the several views, the subject inventionis described schematically in FIG. 3. Here, a plurality of probes 14 aredepicted as GPS-enabled personal navigation devices such as thosemanufactured by TomTom NV (www.tomtom.com). However, any suitable devicewith GPS functionality may be used to generate probe data points,including handheld devices, mobile phones, PDAs, and the like. The probedata points are collected and stored in a probe data table 16 or othersuitable database or repository. The existing digital vector map, inthis example a previously created digital map, is contained in a table18. Of course, the digital vector map 18 can exist as a database or inother suitable form. Trace lines are generated from the rough probe datain table 16 as an initial step. A new line is selected from the probedata table at step 20. The selected line is matched to the digitalvector map at step 22. During this step, each point of the trace linewill be associated with a network element using a map matching method asdescribed in greater detail below. If the matching method is not able toassociate any network element to the trace line, the probe data point ismarked as “unmatched.” All other probe data points are attempted to bematched to the existing network in this manner For trace line segmentswhose data points are not matched to any element of the existingnetwork, these must be split from the network elements and inserted,i.e., connected, via a new or existing junction. This occurs in step 24.In some cases, it is reasonable to use a known or preexisting junction.Junctions may be referred to as intersections in a roadway networkapplication. Sometimes, an existing junction will not be in the correctlocation, and it will be moved as necessary. In some instances, newjunctions will need to be created, according to the techniques describedbelow.

Once the matching and junction steps 22, 24 have been completed, thetrace line segments are merged with the associated network elements atstep 26. This is described in greater detail below, in which mergealgorithms and methodology are utilized. Finally, to reduce the numberof shape points, it is possible to simplify the network element beforeupdating the network table at step 18. This optional simplification stepis indicated at function block 28 and can be accomplished throughvarious techniques, including by application of the well-knownDouglas-Peucker algorithm.

Turning now to FIG. 4, a simplified representation of a digital vectormap is generally indicated at 30. The digital vector map 30 mayrepresent a digital map of a roadway or walking path or the like. Thedigital vector map 30 is represented by a plurality of line segmentsconnected end-to-end by common nodes labeled N1, N2, N3 . . . N8. Thus,the digital vector map 30 exists in this example as a digital map sothat each of the line segments is associated within the coordinatesystem of the map by geo-coded information, as is well known. Here alsoin FIG. 4 exists a trace line, generally indicated at 32. The trace line32 is generated by a plurality of probe data points P1, P2, P3 . . . P8which were generated by radio signal or other wireless technology from aprobe 14 like that described above in connection with FIG. 3.Directionality is represented by the vectors interconnecting data pointsP1-P8 on the trace line 32. The method of this invention is directedtoward improving the digital vector map 30 by determining which portionsof the trace line 32 should be matched with the digital vector map 30,which portions of the trace line 32 represent extended (i.e., new) mapdata which was not previously contained in the digital vector map 30,and where specifically a junction point should be established betweenthe extended portion of the trace line 32 and the digital vector map 30.

Referring now to FIG. 5, the digital vector map 30 and trace line 32 areillustrated, together with assigned values of offset and measure. Theoffset is defined as the shortest distance from a probe data point onthe trace line 32 to the digital vector map 30. The offsets for datapoints P1, P2, P3, P4 and P5 of the trace line 32 are depicted withdouble-ended arrows in FIG. 5. The measure is the length from the firstpoint of the network element(node N1 in the digital vector map 30) tothe orthogonal projection of the trace point to the network element 30.In other words, the measure is the length along the line segments of thedigital vector map 30 up to the point at which the offset measure of aparticular probe data point is taken. In FIG. 5, dimension line 34represents the measure for data point P5 in the trace line 32. Becausethe projected point, i.e., the point at which the offset measurement istaken along a line segment of the digital vector map 30, is in generalnot unique, the measure is also in general not unique. In this case, itmay even be necessary to choose one of several projected points. Tomatch a point Pf Of a trace line p to a network element w, the followingconditions must be observed:

-   -   a. The offset of pl to w must be smaller than a predetermined        maximum offset value.    -   b. There are at least n connected points p_(k), . . . ,        p_(k+n−1) (k≦i<k+n) which have an offset to w smaller than the        predetermined maximum offset value, and where n is a fixed        number greater than or equal to 2.    -   c. For the measures m(p_(j), w), m(p_(l), w) of the points p_(j)        and p_(l) to the network element w, m(p_(j), w)≦m(p_(l), w) if        k≦j<l<k+n.

Thus, it is possible that more than one element in the digital vectormap 30 fulfills these conditions. For example, the digital vector map 30may contain digital vector map elements which are very close together,and for which a data point in the trace line 32 is near to both. Inorder to match the trace line 32 to the digital map, a strategy isneeded to discern the better network element to match the trace line 32.As one strategy example, the network element with the smallest offset ofthe first point in a sequence of the connected points which fulfill theconditions may be used. In a case of bidirectional map matching, it maythen be necessary to modify condition (c.) above.

For the data points P1, P2, P3, P4 and P5 of the trace line 32, theseare matched to the line segments. However, the data points P6, P7 and P8are not matched because the offset of these points is larger than thepredetermined maximum offset value. The predetermined maximum offsetvalue can be selected according to any conditions or specificationsestablished beforehand. Various techniques may be employed to choose thebest network element in any given situation. One possible strategy maybe to implement a kind of hysteresis effect. Another possibility is touse the direction, i.e., heading, to the adjacent previous trace point.Using the latter directional strategy it is possible to set n=1. Ofcourse, it is possible to use both strategies (hysteresis and heading)together.

Through the map matching techniques described above, the trace line 32may be divided into several segments or branches which have the samematched network element (data points P1-P5) or which are unmatched toany network element (data points P6-P8). Contrarywise, the matchednetwork element 30 is divided into one segment which is matched to thetrace line 32 until two segments which are not matched to the trace line32. The objective is to merge the matched segments of the trace line 32with the associated portions of the line segments. Or said another way,the objective is to replace or relocate the network element 30 through acomputed centre-line as described in detail below. Therefore, it isnecessary to determine the location where the line segments in thedigital vector map 30 should be split so as to propagate therefrom a newor extended portion of the network as represented by trace line datapoints P6-P8. At this point, a new junction will be inserted.

There are various methods or techniques to determine the split point orjunction. One simple technique to find the junction node is to use thelast point of the trace line 32 which is matched to the network element30. In the example of FIGS. 7 and 8, probe data point P5 along the traceline 32 is the last point of the trace line 32 which is matched to thenetwork element 30. This point is projected to the closest point on thenetwork element 30, which projection coincides with the offset distancemeasurement. Junction point “r” is calculated as the weighted meanbetween the projected point lying along the network element 30 and theprobe data point P5. Weights are set for both the trace line 32 and theline segment(s) in the digital vector map 30.

A weight can be set also for junctions J of the line segments w, i.e.,for junctions N1 and N8 of the network element 30 Assigning junctions Ja weight more easily allows the algorithm to compute or move junctionsJ. However this is an optional feature as exemplified in the currentversion of the subject algorithm where no particular weights areassociated to the junctions. In cases where junction weight is desired,the weight of the junctions can computed from the weight of the adjacentline segments w, or alternatively from a separate weight assignmenttechnique. Moreover, it is possible to use a finer segmentation of theweight of a line segment w. In such circumstances, it may be helpful toassociate different parts of a line segment w with different weights.For example, one could associate the weight to the individual shapepoints SP in the line segment w. Another possibility to associate aweight to parts of a line segment w is to associate to each line segmentw a list of weight values together with a measure range. Of course, manyother variations are also possible. For simplicity, the weight of thetrace line 32 may be set at one. The weight of the network element 30may be established in various ways, but is here set as the number ofprevious traces from which the digital vector map element 30 wascreated. In these examples, it is assumed that the digital vector map 30was created from two prior trace line events. As a result, the weightfor the digital vector map 30 is two in this example. If, for example,the digital vector map 30 were the result of 15 or 20 or 25 prior tracelines, then the weight of the digital vector map 30 would be set at 15or 20 or 25. The mean at which the split point r is established may becalculated as shown in FIG. 7, wherein the letter x represents the lineweight for the digital vector map 30. In this example, wherein the lineweight of the digital vector map 30 equals 2, point r is spacedone-third (i.e., 1/(2+1)) of the offset distance from the digital vectormap 30. In other words, probe data point P5 is the last point of thetrace line 32 matched to the network element 30, and a weighted meancalculation places the new junction point or node r a distance of ⅓ fromthe original network element 30.

Referring still to FIG. 5, the point r may be a good choice for ajunction point, i.e., the point at which the unmatched data points P6,P7 and P8 of the trace line 32 intersect the digital vector map 30.However, the technique described above for identifying the junctionpoint r may not be suitable in all situations or for all types ofapplications. An alternative technique is to search for the point alongthe digital vector map 30 with the highest measure and with an offset tothe last-matched point along the trace line (point P5 in our example)smaller than the predetermined maximum offset value. If the measure ofthis point is larger than the measure of the projected point (i.e.,point at which the offset measure touches the digital vector map 30),then it may be preferable to use this larger point (N6) to compute thesplit point or junction point. In FIG. 6, this is network data point P6rather than data point N5 if it is assumed that the offset of point N6relative to P5 is still smaller than the predetermined maximum offsetvalue. In this case, the new junction point “s” can be computed in thesame way as a weighted mean of the point and its projection to the traceline 32. This is illustrated in FIG. 6 by reference to the point s as anew junction. Therefore, depending upon the predetermined maximum offsetvalue, different split points or junction points may be calculated.

Practically speaking, however, it may be necessary to consider manydifferent cases. For example, there may be a contrary succession of thepoints, or there may be an end of the trace line 32 or of the networkelement 30. Sometimes, it is possible to use a preexisting junctionwhich is near the computed one. Computing the correct junction pointwill have a significant influence on the digital vector map 30 as it isupdated. Those of skill will understand that many variations can beimplemented in connection with the creation, modification or selectionof junction points. It may be advisable under some circumstances toinsert additional probe data points in the critical areas of the traceline 32 and/or the network element 30. Alternatively, junction pointscan be computed without reliance upon the probe data points whatsoeverusing purely mathematical calculations or subjective standards or byreferring to supplemental reference data.

Once the junction point has been identified, it is necessary to formallysplit the digital vector map element 30. This may be accomplished byadopting the presumed junction points as an actual node in the linesegment, as illustrated in FIG. 8. In FIG. 8, the unmatched part of thedigital vector map 30 consists of its data points P6, P7 and P8. Thedigital vector map 30 is thus split at its new junction point s. Theunmatched part of the trace line 32 is then easily supplemented to thenetwork. It is necessary only to connect the network element 30 frompoint N7 to the new junction points.

Before completing the update operation, line segment 30 is replaced orrelocated to a computed centre-line. I.e., the trace line 32 is mergedwith the digital vector map 30 by creating a centre-line between thematched part of the trace line 32 and the digital vector map element 30.To compute the new centre-line, each matched data point of the traceline 32 (i.e., data points P1, P2, P3, P4 and P5) are projected to thedigital vector map element 30 using the offset distance methodologydescribed above. For each such offset distance, the weighted mean iscomputed between the two points after the manner described above inconnection with FIG. 7. Again, the weight of the trace line 32 may beset to 1, whereas the weight of the digital vector map element 30 is thenumber of prior traces from which it was created. Therefore, the mergerof point P5 results in the new data point r, which becomes a node forthe centre-line. To obtain further data points and thereby enhanceaccuracy of the network data, matched points from the digital vector map30 (i.e., N2, N3, N4 and N5) are matched to the trace line 32 usingsimilar orthogonal projection as shown in FIG. 8. The weighted mean iscomputed for these offsets as well, as represented by the node pointsplaced along the respective offsets.

All of these newly computed mean points are connected as line segmentswhich together comprise the centre-line. The weight of the computedcentre-line is now the sum of the weights of the prior digital vectormap 30 and trace line 32 or the continuing example 3. Thus, the nexttime probe data points are matched to the updated digital vector map,which will now be represented by broken lines 36, the line weight willbe 3. After this step, the updated network element 36 then replaces theprevious digital vector map 30 in the table 18 with its node points andcomputed weight. Therefore, with each matched trace line 32, the updatednetwork element line 36 contains more and more data points or nodes.Thus, it may be helpful to remove some of these points throughsimplifying the geometry. For that purpose, the Douglas-Peuckeralgorithm may be used, which is well documented.

Those of skill in this field may envision various improvements andextensions of this technology. For example, with these techniques, it isforeseeable to incorporate the computation of several road attributeslike average speed, road classification, altitude and slope values.Computing of the altitude, for example, can be understood simply as anadditional attribute to an ordinary two-dimensional map, or as anadditional dimension. In the latter case, the whole map can beconsidered as a three-dimensional map. The whole network generation andrefinement process can be applied on this three-dimensional map. Whenmatching a three-dimensional trace to a three-dimensional map, athree-dimensional centre-line is computed and so on. Of course one hasto assume that for all trace points and also for the pre-existing mapaltitude values are available. This is in the first case not necessarybecause it is possible to compute attributes also with incomplete data.Furthermore, confidence models can be developed for the generatedgeometry as well as the several attributes. Detection of turn behaviorat crossings and branchings can also be implemented in connection withsuitable data modeling to represent the turn behavior. Furthermore, stopsigns and traffic lights can be inferred or detected. With a suitableextension of these techniques, a bidirectional network can be generated.By these techniques, network elements generated from old data can bekept up to date without overloading data storage or data processingresources.

The foregoing invention has been described in accordance with therelevant legal standards, thus the description is exemplary rather thanlimiting in nature. Variations and modifications to the disclosedembodiment may become apparent to those skilled in the art and fallwithin the scope of the invention. Accordingly the scope of legalprotection afforded this invention is defined only by the followingclaims.

What is claimed is:
 1. A computer-implemented method for generating,refining and extending digital vector maps using GPS traces from probedata, comprising: providing, by a processor, a digital vector map havinga plurality of nodes spatially associated within a coordinate system,each node having at least one line segment extending therefrom;associating, by the processor, each line segment in the digital vectormap with a weight value, wherein the weighting of each line segment isbased on a number of previous probe traces associated with each linesegment; collecting, by the processor, at least one GPS trace from aplurality of sequentially transmitted probe data points; establishing,by the processor, a map matching criteria; comparing, by the processor,each probe data point along the GPS trace to at least one line segmentin the digital vector map using the map matching criteria; designating,by the processor, as “matched” each probe data point along the GPS tracethat meets the map matching criteria while designating as “unmatched”each probe data point along the GPS trace that fails the map matchingcriteria; associating, by the processor, the portion of the GPS tracecontaining matched probe data points to the respective line segment(s)of the digital vector map; computing, by the processor, a centre-linebetween the respective line segment and the portion of the GPS tracecontaining matched probe data points using the weight value of the linesegment; replacing, by the processor, the line segment through thecentre-line; and creating, by the processor, a new line segment in thedigital vector map with the portion of the GPS trace containingunmatched probe data points; the method further comprising the steps of:determining, by the processor, a split point based on the last matchedprobe data point and a projected point on the line segment of thedigital vector map by projecting a last matching probe point to a closetpoint on a respective line segment associated with the last matchingprobe point; splitting, by the processor, the digital vector map byproviding a new node at this point; and connecting, by the processor,the new node with the next node in the digital vector map.
 2. The methodof claim 1 further including simplifying the updated digital vector map.3. The method of claim 1 wherein said step of simplifying the updateddigital vector map includes applying the Douglas-Peucker algorithm. 4.The method of claim 1 wherein the digital vector map is a unidirectionalnetwork.
 5. The method of claim 1 wherein the digital vector map is abidirectional network.
 6. The method of claim 1 further comprisingcomputing attributes of the updated digital vector map.
 7. The method ofclaim 6, wherein said step of computing attributes includes computing aroad class of the line segments.
 8. The method of claim 1 furtherincluding removing line segments from the digital vector map which havea weight value below a predetermined threshold value in apost-processing operation.
 9. The method of claim 1, wherein thedesignation is based on a calculated offset distance between each probedata point and the respective line segment.
 10. The method of claim 1further comprising providing the digital vector map to one or morenavigation system to assist in at least one navigation service.
 11. Themethod of claim 2, wherein the projection uses a calculated weightedmean.
 12. A non-transitory computer-readable medium which stores a setof instructions which when executed performs a method for generation,refining and extending digital vector maps using GPS traces from probedata, the method executed by the set of instructions comprising:providing a digital vector map having a plurality of nodes spatiallyassociated within a coordinate system, each node having at least oneline segment extending therefrom; associating each line segment in thedigital vector map with a weight value, wherein the weighting of eachline segment is based on a number of previous probe trace associatedwith each line segment; collecting at least one GPS trace from aplurality of sequentially transmitted probe data points; establishing amap matching criteria; comparing each probe data point along the GPStrace to at least one line segment in the digital vector map matchingcriteria; designating as “matched” each probe data point along the GPStrace that meets the map matching criteria while designating as“unmatched” each probe data point along the GPS trace that fails the mapmatching criteria; associating the portion of the GPS trace containingmatched probe data points to the respective line segment(s) of thedigital vector map; computing a centre-line between the respective linesegment and the portion of the GPS trace containing matched probe datapoints using the weight value of the line segment; replacing the linesegment through the centre-line; and creating a new line segment in thedigital vector map with the portion of the GPS trace containingunmatched probe data points; the method further comprising the steps of:determining a split point based on the last matched probe data point anda projected point on the line segment of the digital vector map byprojecting a last matching probe point to a closet point on a respectiveline segment associated with the last matching probe point; splittingthe digital vector map by providing a new node at this point; andconnecting the new node with the next node in the digital vector map.13. The computer-readable medium of claim 12 further comprisingproviding the digital vector map to one or more navigation systems toassist in at least one navigation service.
 14. The computer-readablemedium of claim 12, wherein the projection uses a calculated weightedmean.
 15. A non-transitory computer-readable medium which stores a setof instructions which when executed performs a method for generating,refining and extending digital vector maps using GPS traces from probedata, the method executed by the set of instructions comprising:providing a digital vector map having a plurality of nodes spatiallyassociated within a coordinate system, each node having at least oneline segment extending therefrom; associating each line segment in thedigital vector map with a weight value, wherein the weighting of eachline segment is based on a number of previous probe traces associatedwith each line segment; collecting at least one GPS trace from aplurality of sequentially transmitted probe data points; establishing amap matching criteria; comparing each probe data point along the GPStrace to at least one line segment in the digital vector map using themap matching criteria; designating as “matched” each probe data pointalong the GPS trace that meets the map matching criteria whiledesignating as “unmatched” each probe data point along the GPS tracethat fails the map matching criteria; associating the portion of the GPStrace containing matched probe data points to the respective linesegment(s) of the digital vector map; computing a centre-line betweenthe respective line segment and the portion of the GPS trace containingmatched probe data points using the weight value of the line segment;replacing the line segment through the centre-line; and creating a newline segment in the digital vector map with the portion of the GPS tracecontaining unmatched probe data points; determining a split point basedon the last matched probe data point and a projected point on the linesegment of the digital vector map by projecting a last matching probepoint to a closest point on a respective line segment associated withthe last matching probe point; splitting the digital vector map byproviding a new node at this point; and connecting the new node with thenext node in the digital vector map.